ExactBoost: Directly Boosting the Margin in Combinatorial and Non-decomposable Metrics. - Daniel Csillag; Carolina Piazza; Thiago Ramos; João Vitor Romano; Roberto I. Oliveira 001; Paulo Orenstein (AISTATS, 2022)

AmnioML: Amniotic Fluid Segmentation and Volume Prediction with Uncertainty Quantification. - Daniel Csillag; Lucas Monteiro Paes; Thiago Ramos; João Vitor Romano; Rodrigo Schuller; Roberto de Beauclair Seixas; Roberto I. Oliveira 001; Paulo Orenstein (AAAI, 2023)

BlockBoost: Scalable and Efficient Blocking through Boosting. - Thiago Ramos; Rodrigo Loro Schuller; Alex Akira Okuno; Lucas Nissenbaum; Roberto I Oliveira; Paulo Orenstein (AISTATS, 2024)

PersonalizedUS: Interpretable Breast Cancer Risk Assessment with Local Coverage Uncertainty Quantification. - Alek Fröhlich; Thiago Ramos; Gustavo Cabello; Isabela Buzatto; Rafael Izbicki; Daniel Guimarães Tiezzi (CoRR, 2024)

Split Conformal Prediction and Non-Exchangeable Data. - Roberto I. Oliveira 001; Paulo Orenstein; Thiago Ramos; João Vitor Romano (J. Mach. Learn. Res., 2024)

PersonalizedUS: Interpretable Breast Cancer Risk Assessment with Local Coverage Uncertainty Quantification. - Alek Fröhlich; Thiago Ramos; Gustavo Motta Cabello Dos Santos; Isabela Panzeri Carlotti Buzatto; Rafael Izbicki; Daniel Guimarães Tiezzi (AAAI, 2025)

Epistemic Uncertainty in Conformal Scores: A Unified Approach. - Luben M. C. Cabezas; Vagner S. Santos; Thiago Ramos; Rafael Izbicki (UAI, 2025)